How to Install and Uninstall paraclu Package on Ubuntu 21.10 (Impish Indri)

Last updated: May 03,2024

1. Install "paraclu" package

This guide let you learn how to install paraclu on Ubuntu 21.10 (Impish Indri)


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                paraclu
            
                    
    
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2. Uninstall "paraclu" package

This guide covers the steps necessary to uninstall paraclu on Ubuntu 21.10 (Impish Indri):


    
        
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                sudo apt remove
            
                        
                paraclu
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the paraclu package on Ubuntu 21.10 (Impish Indri)

Package: paraclu
Architecture: amd64
Version: 9-3
Priority: optional
Section: universe/science
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Med Packaging Team
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 41
Depends: libc6 (>= 2.14), libgcc-s1 (>= 3.0), libstdc++6 (>= 5.2)
Filename: pool/universe/p/paraclu/paraclu_9-3_amd64.deb
Size: 11372
MD5sum: 4035905561c75a373fa0a8cdbde638e6
SHA1: 41c5ee4c78a3765a932b00a0d84467f5b90d77c1
SHA256: 84d18f98818b96c917bf873bb5fee4b32ca0d6abb25cfcab9621a8552d2717d5
SHA512: ffe7eb9a3e371c9a16f059b357d05b29b574ae86b2c9c2d9d10413927fa35aa15770d728df039887f985000382b42cb2d99c938609779dc454b73978801c140c
Homepage: http://cbrc3.cbrc.jp/~martin/paraclu/
Description-en: Parametric clustering of genomic and transcriptomic features
Paraclu finds clusters in data attached to sequences. It was first
applied to transcription start counts in genome sequences, but it
could be applied to other things too.
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Paraclu is intended to explore the data, imposing minimal prior
assumptions, and letting the data speak for itself.
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One consequence of this is that paraclu can find clusters within
clusters. Real data sometimes exhibits clustering at multiple scales:
there may be large, rarefied clusters; and within each large cluster
there may be several small, dense clusters.
Description-md5: f98735ee4cee799306e80fba3779244f